Blog or Site Analytics

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While monitoring access related to various campaigns of events related to Tech professionals in the Bay Area, I see following typical usage:

Internet Access by Tech Professionals

Observations:

1. Highest usage is around lunch hour . May be many tech professionals read events and news during over lunch.

2. Third ( I will talk about the second at the end of the post) highest usage is around morning 8-9 which is logical. Its warming up before the actual work.

3. During the morning hours these access is least. This seems to be most productive time from the work point of view.

5. I am surprised not to see another peak around the time when the professionals leave the office. May be they just want to leave as soon as work is done or they already get delayed in work and would like to beat the traffic (which is impossible in the bay area)

6. The most interesting fact is the second highest access is around mid-night. Is it due to some bots accessing the site or the tech professionals in the bay area work till mid night and then read the news / event updates just before hitting the bed?

When PR hits the market, its impact is supposed to be felt in various channels, one of which would be on incoming visits to site and blogs or apps downloads. When monitoring such impact, it is very important to measure the momentum also. Whether it is for GITPRO events or for Website or my personal blog, I use Google analytics to mainly monitor:

1. Trend in the number of visits:

2. Where are the users coming from? demography(location), as well as source (mail / ip / site)

3. Entry link? which links are the first one that they visit?

4. How long they stay on the site?

5. Which links do they visit?

6. Any comments posted by the users?

7. How many are repeat and how many are new users?

And repeat this very often. Particularly, there would be an upside whenever there is a marketing PR wave or any event occurs that triggers the incoming visits. However, in a day or two the trend would start tapering down. However, with an effective campaign, the average users should be more than pre-campaign. Otherwise it would be one-day fame . Of course, one needs to analyze the drop outs too.